Dev tools · alternatives · 2026
24 alternatives to Achilles – Automatic profiling and C++ optimization of Python via LLMs
Hey HN! We built Achilles, a tool that automatically accelerates your Python code. It identifies performance bottlenecks, rewrites those functions in optimized C++, and seamlessly patches them into your running program—without you changing a single line of code. In CPU-intensive, loop-heavy tasks, we've observed performance improvements of 100-1000x. Achilles can be installed via pip and works with just a single command. We'd appreciate your feedback, and feel free to give us a star if you find it interesting!
Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.
- 1
Hi everyone, I built PyXL — a hardware processor that executes a custom assembly generated from Python programs, without using a traditional interpreter or virtual machine. It compiles Python -> CPython Bytecode -> Instruction set designed for direct hardware execution. I’m sharing an early benchmark: a GPIO test where PyXL achieves a 480ns round-trip toggle — compared to 14-25 micro seconds on a MicroPython Pyboard - even though PyXL runs at a lower clock (100MHz vs. 168MHz). The design is stack-based, fully pipelined, and preserves Python's dynamic typing without static type restrictions.…
2025 · runpyxl.com · its alternatives →
- 2
beLow▲176Inline insights with C/C++ that shows CPU, memory, energy
Dec 2025 · wedolow.com · its alternatives →
- 3
Hi HN! We’re Adrien and Kanav. We met at our previous job, where we spent about a third of our lives combating a constant firehose of bugs. In the hope of reducing this pain for others in the future, we’re working on automating debugging. We’re currently working on a platform that ingests logs and then automatically reproduces, root causes and ultimately fixes production bugs as they happen. You can see some of our work on this here - https://news.ycombinator.com/item?id=39528087 As we were building the root-cause phase of our automated debugger, we realized that we developed…
2024 · github.com · its alternatives →
- 4
An experimental Python-to-C transpiler and domain specific language for embedded high-performance computing - zanellia/prometeo
2021 · github.com · its alternatives →
- 5
2014 · github.com · its alternatives →
- 6
DEPRECATED StackImpact Python Profiler - Production-Grade Performance Profiler: CPU, memory allocations, blocking calls, exceptions, metrics, and more - stackimpact/stackimpact-python
2017 · github.com · its alternatives →
- 7
Modern scheduling library for Python. Contribute to Miksus/rocketry development by creating an account on GitHub.
2022 · github.com · its alternatives →
- 8
Hi HN, Over the past few months, I've been building `dsc`, a tensor library from scratch in C++/CUDA. My main focus has been on getting the basics right, prioritizing a clean API, simplicity, and clear observability for running small LLMs locally. The key features are: - C++ core with CUDA support written from scratch. - A familiar, PyTorch-like Python API. - Runs real models: it's complete enough to load a model like Qwen from HuggingFace and run inference on both CUDA and CPU with a single line change[1]. - Simple, built-in observability for both Python and C++. Next on the roadmap is…
2025 · github.com · its alternatives →
- 9
I've been working on Fast LiteLLM - a Rust acceleration layer for the popular LiteLLM library - and I had some interesting learnings that might resonate with other developers trying to squeeze performance out of existing systems. My assumption was that LiteLLM, being a Python library, would have plenty of low-hanging fruit for optimization. I set out to create a Rust layer using PyO3 to accelerate the performance-critical parts: token counting, routing, rate limiting, and connection pooling. The Approach - Built Rust implementations for token counting using tiktoken-rs - Added lock-free data…
Nov 2025 · github.com · its alternatives →
- 10
Simple Python Calculation Engine. Contribute to bsdz/calcengine development by creating an account on GitHub.
2021 · github.com · its alternatives →
- 11
Forge Agent▲113Swarm Agents That Turn Slow PyTorch Into Fast GPU Kernels
Jan 2026 · rightnowai.co · its alternatives →
- 12
I built Copapy as an experiment: Can Python be used for hard real-time systems? Instead of an interpreter or JIT, Copapy builds a computation graph by tracing Python code and uses a custom copy-and-patch compiler. The result is very fast native code with no GC, no syscalls, and no memory allocations at runtime. The copy-and-patch compiler currently supports x86_64 as well as 32- and 64-bit ARM. It comes as small Python package with no other dependencies - no cross-compiler, nothing except Python. The current focus is on robotics and control systems in general. This project is early but…
Feb 2026 · github.com · its alternatives →
- 13
A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python. - reiinakano/xcessiv
2017 · github.com · its alternatives →
- 14
Txeo is a lightweight and intuitive C++ wrapper for TensorFlow, designed to simplify TensorFlow C++ development while preserving high performance and flexibility. Built entirely with Modern C++, Txeo allows developers to use TensorFlow with the ease of a high-level API, eliminating the complexity of its low-level C++ interface.
2025 · github.com · its alternatives →
- 15PA
I’m sure many of you are familiar, but there’s a treacherous gap between finding (or building) a model that works in PyTorch, and getting that deployed into your application, especially in consumer-facing applications. I’ve been very interested in solving this problem with a great developer experience. Over time, I gradually realized that the highest-impact thing to have was a way to go from existing Python code to a self-contained native binary—in other words, a Python compiler. I was already pretty familiar with a successful attempt: when Apple introduced armv8 on the iPhone 5s, they…
2025 · blog.fxn.ai · its alternatives →
- 16
I want to share a really dumb, but very practical project I have packaged this summer, to perform operations on strings much faster. I was using Python to work with a multi-terabyte newline-delimited file. Reading, splitting, and shuffling it was a nightmare. So, I wrapped a trivial hardware-friendly heuristic I've been using for the last few years into a CPython library. The part I enjoyed the most is implementing SIMD behavior without SIMD instructions... Using 64-bit words to work at 8-bit granularity. Unlike conventional SIMD, the code would remain the same for ~~almost~~ any hardware.…
2023 · ashvardanian.com · its alternatives →
- 17
Hello, I have several years of experience as a Python developer, and during that time, I've worked on intricate applications dealing with large volumes of data. One frequent challenge I faced was benchmarking the application and identifying performance bottlenecks. While there are some excellent Python profiling tools available, they can be quite daunting for beginners. The utility I have developed simplifies this process, making it as straightforward as possible to transition from slow code to a detailed flame chart. I would greatly appreciate your feedback!
2023 · github.com · its alternatives →
- 18
Quick note on how it works and how I've done my batch embedding engine IgniteMS. The whole thing runs as one process using Rust, reading input, tokenizing, packing batches, keeping the queue full. TensorRT handles inference. Python is only as a wrapper. I built it this way because when you use more than couple of GPUs, the GPUs stop being the problem. CPU cannot feed them fast enough. One A100 can go through batches faster than Python can tokenize and feed, so the GPU just sits there idle waiting for work. Most of my time went into optimizing this. At 8 GPUs that was basically the entire…
Jun 2026 · github.com · its alternatives →
- 19
Grant Sanderson (3Blue1Brown) created Manim, the Python library he uses to make the math animations in his videos. We reimplemented Manim with the same Python API, but the implementation underneath is Rust, connected to Python through PyO3. The Rust code uses wgpu, so rendering happens on the GPU. To run it in the browser, we compiled the Rust parts to WebAssembly so the PyO3 extension loads in Pyodide. In the browser, wgpu targets the WebGPU API, so animations render in real time on your GPU through the browser. The editor is Monaco (the editor that powers VS Code) with a live preview:…
Jul 2026 · studio.academa.ai · its alternatives →
- 20
A langgraph based workflow with a C++ CUDA suite to optimize CUDA kernels - bertaye/agentic-cuda-optimizer
27d ago · github.com · its alternatives →
- 21
We built RapidFire AI, an open-source Python tool to speed up LLM fine-tuning and post-training with a powerful level of control not found in most tools: Stop, resume, clone-modify and warm-start configs on the fly—so you can branch experiments while they’re running instead of starting from scratch or running one after another. - Works within your OSS stack: PyTorch, HuggingFace TRL/PEFT), MLflow. - Hyperparallel search: launch as many configs as you want together, even on a single GPU - Dynamic real-time control: stop laggards, resume them later to revisit, branch promising configs in…
2025 · github.com · its alternatives →
- 22
Self-contained C/C++ profiler library for Linux. Contribute to cyrus-and/prof development by creating an account on GitHub.
2015 · github.com · its alternatives →
- 23
GitHub▲7BERT, Tokenizer, Python, WordPiece, pybind11,C++,Flash,Trie
2025 · github.com · its alternatives →
- 24
2024 · gitlab.com · its alternatives →
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- StackImpact – Python Production Profiler: CPU, Memory, Exceptions alternatives
Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →